Síndrome metabólica e associação com nível socioeconômico em escolares

Revista CEFAC ISSN: 1516-1846 [email protected] Instituto Cefac Brasil

Durães Cruz, Igor Rainneh; Antunes Freitas, Daniel; Soares, Wellington Danilo; Mota Mourão, Daniella; Aidar, Felipe José; Carneiro, André Luiz SÍNDROME METABÓLICA E ASSOCIAÇÃO COM NÍVEL SOCIOECONÔMICO EM ESCOLARES Revista CEFAC, vol. 16, núm. 4, julio-agosto, 2014, pp. 1294-1302 Instituto Cefac São Paulo, Brasil

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METABOLIC SYNDROME AND ITS ASSOCIATION WITH SOCIO-ECONOMIC LEVEL IN STUDENTS Síndrome metabólica e associação com nível socioeconômico em escolares Igor Rainneh Durães Cruz(1), Daniel Antunes Freitas(2), Wellington Danilo Soares(3), Daniella Mota Mourão(4), Felipe José Aidar(5), André Luiz Carneiro(6)

ABSTRACT Purpose: to investigate the association between socioeconomic status and the presence of metabolic syndrome (MS) in public schools in the city of Montes Claros-MG. Methods: this is a cross-sectional study, analytical. We evaluated 382 children between 10 and 16 years from the cluster sampling. Socioeconomic status was divided into high and low and MS was diagnosed using the criteria of the International Diabetes Federation. For data analysis, we used the chi-square test (p p 90° age is essential for the diagnosis of the syndrome. Below 10 years, the diagnosis of MS should not be done, but the child should be counseled about the need for weight loss and a change of lifestyle. For those over 10 years, the MS diagnosis can be conducted and, therefore, there must be abdominal obesity and the presence of two or more of the following factors: TG > 150 mg / dL, HDL < 40 mg / dL, Gly > 100 mg / dL, SBP ≥ 130 and DBP ≥ 85 mmHg 20. For adolescents older than 16 years, the criteria used were those for adults5. All subjects were evaluated by two physical education teachers with minimum experience of 30 ratings, and “r” Pearson intra - raters was 0.975 and between subjects was 0.967. The period of data collection occurred in four days. On the first day the researcher sought each drawn school and presented the objectives of the research to the director, who subsequently informed the physical

Rev. CEFAC. 2014 Jul-Ago; 16(4):1294-1301

education teachers about the study procedures. In possession of the identification of age, sex, class, period of study and course work, the students were drawn to participate in the study. On the second day, the researcher presented each student with a suit-free consent form to be completed by parents or guardians, with a commitment to return the form. The next day, being the third day, and now in possession of the consent form, the socioeconomic questionnaires were administered along with hemodynamic and anthropometric evaluation. On the fourth day, the students attended the laboratory for blood sampling after fasting for 12 hours before the exercise. For data analysis, we used the statistical program Statistical Package for Social Sciences (SPSS 20.0 for Windows ®). Descriptive statistics was done by means of the measures of central tendency mean ± standard deviation (M ± SD). The Kolmogorov Smirnov test of normality was conducted, given the sample size. After the normality test, the chi-square test was equally conducted in order to associate the prevalence of MS with the proposed nutritional status. The magnitude was calculated from the odds ratio (OR), with confidence intervals of 95 % (95% CI).

„„ RESULTS Table 1 shows the descriptive values of the investigated sample according to the CSE. The CSEA consisted of 37 students, 16 (43.2 %) boys and 21 girls (56.8 %), while CSEB showed a greater amount of 345 school children, 135 (39.1 %) boys and 210 (60.9 %) girls. Most of the population is between 11 and 12 years for CSEA and 11 to 14 for CSEB. The MC and E were higher for CSEA than for CSEB. In observation of nutritional status, 75.4% of students presented as eutrophic (CSEA: 78.4%; CSEB: 75.1%), 17.3% were overweight (CSEA: 16.2%; CSEB: 17.4%) and 7.3% were obese (CSEA: 5.4%; CSEB: 7.5%). Regarding education of the population investigated in both groups, the predominant primary education: 67.6 % in CSEA and 87.5 % in CSEB. The skin color was selfreported, the CSEA consisted of 24 (64.9 %) mixed, 4 (10.8%) blacks and 6 (16.2%) were white, while CSEB gathered in 202 (58.6 %) mixed, 55 (15.9%) blacks and 46 (13.4%) were white.

Metabolic syndrome and socioeconomic 

Table 2 presents the prevalence of students regarding the criteria for diagnosis of MS by CSE. Regarding CA, 8.4% of students from CSEB had values above the established (CI: 0.88 to 0.46, p = 0.067). As for BP, only CSEB showed changes in SBP and 0.6 % (CI: 0.98 to 1, p = 0.642) and 0.3 % with PAD (CI: 0.99 to 1, p = 0.743). The TG 2.6% of students from CSEB is above the reference values (CI: 0.95-0.99, p = 0.320). Only 1.4% of students from CSEB showed hyperglycemia (CI: 0.97-0.99, p = 0.461).

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On the levels of HDL-C, 5.4% of students from CSEA and 18.8% of the school CSEB presented below the reference values, which showed a significant association (p = 0.041) indicating that CSEB is less likely to be active than CSEA (OR = 3.48, CI: 0.89 to 13.65). These results demonstrate that those children belonging to the group CSEB changes in more than three criteria thus increasing the chances for diagnosis of MS. Table 3 shows the diagnosis of MS in 8.7% of CSEB investigated, the prevalence being higher among girls (10.4%) compared to boys (4 %).

Table 1 - Description of the school according to socioeconomic status Variables Gender Male Female Age (Years) 10 11 12 13 14 15 16 Body Mass (Kg) Stature (m) BMI (Kg/m2) Eutrofic Overweight Obese Education 5ª Serie 6ª Serie 7ª Serie 8ª Serie 1º Year 2º Year 3º Year Race Brown Black Mulatto Indigenous Yellow White

CSEA

Socioeconomic Classification CSEB

Total

16 (43,2%) 21 (56,8%)

135 (39,1%) 210 (60,9%)

151 (39,5%) 231 (60,5%)

4 (10,8%) 7 (18,9%) 8 (21,6%) 2 (5,4%) 4 (10,8%) 4 (10,8%) 8 (21,6%) 50,12 ± 11,47 1,57 ± 0,11

29 (8,4%) 67 (19,4%) 58 (16,8%) 66 (19,1%) 63 (18,3%) 30 (8,7%) 32 (9,3%) 49,35 ± 13,72 1,55 ± 0,11

33 (8,6%) 74 (19,4%) 66 (17,3%) 68 (17,8%) 67 (17,5%) 34 (8,9%) 40 (10,5%) 49,42 ± 13,51 1,55 ± 0,10

27 (73%) 8 (21,6%) 2 (5,4%)

254 (73,6%) 64 (18,6%) 27 (7,8%)

281 (73,6%) 72 (18,8%) 29 (7,6%)

7 (18,9%) 10 (27%) 4 (10,8%) 4 (10,8%) 4 (10,8%) 6 (16,2%) 2 (5,4%)

101 (29,3%) 58 (16,8%) 73 (21,2%) 70 (20,3%) 23 (6,7%) 16 (4,6%) 4 (1,2%)

108 (28,3%) 68 (17,8%) 77 (20,2%) 74 (19,2%) 27 (7,1%) 22 (5,8%) 6 (1,6%)

24 (64,9%) 4 (10,8%) 1 (2,7%) 1(2,7%) 1 (2,7%) 6 (16,2%)

202 (58,6%) 55 (15,9%) 14 (4,1%) 14 (4,1%) 14 (4,1%) 46 (13,4%)

226 (59,2%) 59 (15,4%) 15 (3,9%) 15 (3,9%) 15 (3,9%) 52 (13,6%)

CSEA: High Socioeconomic Conditions; CSEB: Low Socioeconomic Conditions.

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Cruz IRD, Freitas DA, Soares WD, Mourão DM, Aidar FJ, Carneiro AL

Table 2 - Description of the criteria of the metabolic syndrome and prevalence (%) with 95% confidence according to socioeconomic status Criteria CA (cm) Desirable Changed SBP (mmHg) Desirable Neighboring DBP (mmHg) Desirable Changed TG (mg/dL) Desirable Changed HDL-c (mg/dL) Desirable Changed GlI (mg/dL) Desirable Changed

Socioeconomic Classification CSEB OR

IC (95%)

37 (100%) --

316 (91,6%) 29 (8,4%)

0,91

0,88-0,46

0,067

37 (100%) --

343 (99,4) 2 (0,6)

0,99

0,98-1,00

0,642

37 (100%) --

344 (99,7%) 1 (0,3)

0,99

0,99-1,00

0,743

37 (100%) --

336 (97,4%) 9 (2,6%)

0,97

0,95-0,99

0,320

35 (94,6%) 2 (5,4%)

280 (81,2%) 65 (18,8%)

3,48

0,89-13,65

0,041*

37 --

340 (98,6%) 5 (1,4%)

0,98

0,97-0,99

0,461

CSEA

p

CSEA: High socioeconomic status; CSEB: Socioeconomic status Low, OR: Oddsratio; CI: Confidence Interval, P: statistical significance from qui-square Test CA: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, TG: triglycerides, HDL-C: Cholesterol High Density; Gli: Glucose *p p90º are likely to have a sedentary lifestyle and present lipid disorders, type 2 diabetes, hypertension, these being the components of the MS. In this experiment we found a lower prevalence of children with hypertension analyzed separately, DBP and SBP showed no associations with the CSE. Pressure levels are used in the diagnosis of MS and affects between 0.8% and 8.2% of children and adolescents. Cross-sectional studies associate high blood pressure with nutritional status, CA and CSE, since their combination accelerates premature metabolic changes and their evaluation becomes necessary for children whose families are at greater social risk32-34. The diagnosis of hypertension and its inclusion as a parameter in MS detection should take into account age, sex and height 19. The dyslipidemias are disorders in the concentrations of serum lipids, such as an increase in total cholesterol, low density lipoprotein (LDL-C), and TG and reduced HDL- c5. Epidemiological studies show an association between high levels of total cholesterol to the incidence of coronary heart disease at any age; these changes usually begin in childhood and occur silently, with atherosclerotic lesion diagnosed only in adulthood10,12,21. This same result was observed in cross-sectional study involving 419 adults over 20 years old in Eastern Taiwan, which showed that 19.3% of those affected by MS, developed it during childhood and adolescence 35.

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In this study the prevalence of abnormalities to TG and Gly is very small and the CSEB, the most affected people belonging to lower income, are associated with the incidence and CVD mortality, probably because of the accumulation of risk factors (physical inactivity, hypertension, dyslipidemia), overweight being the main factor. In addition, low literacy level limits information pertaining to prophylactic care1,3,4. The increased levels of HDL-C decreased the relative risk for CVD, the ability to perform this reverse cholesterol transport and prevent oxidation and aggregation of the particles of LDL-c in the arterial wall, decreasing the potential of this atherogenic lipoprotein36. In the studied sample, decreased concentrations of HDL-C occurred in 18.8% of the school in CSEB, a result that is higher than that of the cross-sectional study done among children and adolescent who were born in Sāo Paulo State, which totaled 13.8%37. The presence of MS was diagnosed in 8.7% and all of CSEB and studies indicate the prevalence of those affected to be between 4.1% and 17.2% of investigated11-26. The relationship between CSE and MS is close because economic disadvantages are predictive for its occurrence among children and adolescents6,7,13. Investigations cite this disorder may be initiated due to risk factors exposed to the individual, such as low literacy level, obesity, highcalorie foods, sedentary lifestyle and altered lipid profile8,9,12. A limitation of this study was the imbalance of the sample in relation to socioeconomic conditions. Few CSEA schools were obtained because schools or region were not prioritized. The sample was representative of schools in Montes - clarenses due to the sample size calculation that was employed. The results presented here corroborate other investigations. The scarcity of research on the subject was another limiting factor for discussion of the results, which made us to use international benchmarks.

„„ CONCLUSION The CSE contributes significantly to the prevalence of MS, its presence was diagnosed in 8.7% of the schools in CSEB because they present change in more than three items. There is an increasing incidence of MS among children and adolescents, but there is no consensus on the cutoff points for diagnosis in young populations which makes it more difficult to detect and further treatment. In this context, it becomes necessary to conduct further studies in other cities in the north of Minas since this is the first research carried out in this region. Rev. CEFAC. 2014 Jul-Ago; 16(4):1294-1301

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Cruz IRD, Freitas DA, Soares WD, Mourão DM, Aidar FJ, Carneiro AL

RESUMO Objetivo: verificar a associação entre o nível socioeconômico e a presença de síndrome metabólica (SM) em escolares da rede pública da cidade de Montes Claros-MG. Métodos: trata-se de estudo transversal, analítico. Foram avaliados 382 escolares entre 10 e 16 anos, a partir da amostragem por conglomerados. A condição socioeconômica foi dividida em alta e baixa e a SM foi diagnosticada utilizando os critérios da International Diabetes Federation. Para análise dos dados, utilizou-se o teste qui-quadrado (p < 0,05)e oddsratio (com intervalo de 95% de confiança). Resultados: os escolares da classe socioeconômica baixa apresentaram alterações no estado nutricional e nos exames laboratoriais, o que contribuiu para presença da SM em 8,7% escolares. Conclusão: a condição socioeconômica baixa contribui de forma significante para o diagnótico da SM e atua também na incidência dessa patologia, devido os seus pertencentes estarem mais expostos aos fatores de risco. DESCRITORES: Classe Social; Estado Nutricional; Estudantes; Epidemiologia

„„ REFERENCES 1. Drenowatz C, Eisenmann JC, Pfeiffer KA, Welk G, Heelan K, Gentile D, et al. Influence of socioeconomic status on habitual physical activity and sedentary behavior in 8 to 11 year old children. BMC Public Health. 2010;10:214-25. 2. McLaren L. Socioeconomic Status and Obesity. Epidemiol Rev. 2007; 29:29-48. 3. Lawlor DA, Ebrahim S, Smith GD. Socioeconomic position in childhood and adulthood and insulin resistance: cross sectional survey using data from British women’s heart and health study. BMJ. 2002;325:1-5. 4. Tamayo T, Herder C, Rathmann W. Impact of early psychosocial factors (childhoodsocioeconomic factors and adversities) on future risk of type 2 diabetes, metabolic disturbances and obesity: a systematic review. BMC Public Health. 2010;10:525. 5. Faienza MF, Francavilla R, Goffredo R, Ventura A, Marzano F, Panzarino G et al. Oxidative stress in obesity and metabolic syndrome in children and adolescents. Horm Res Paediatr. 2012;78(3):158-64. 6. Xu H, Li Y, Liu A, Zhang Q, Hu X, Fang H et al. Prevalence of the metabolic syndrome among children from six cities of China. BMC Public Health. 2012;12:13. 7. Goodman E, Daniels SR, Morrison JA, Huang H, Dolan LM. Contrasting prevalence of and demographic disparities in the world health organization and national cholesterol education program adult treatment panel iii definitions of metabolic syndrome among adolescents. J Pediatr. 2004;145:445-51. 8. Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Medicine. 2011;9:48-61. Rev. CEFAC. 2014 Jul-Ago; 16(4):1294-1301

9. Rodrigues AN, Perez AJ, Pires JGP, Carletti L, Araújo MTM, Moyses MR, et al. Cardiovascular risk factors, their associations and presenceof metabolic syndrome in adolescents.J Pediatr. 2009;85:55-60. 10. Leitão MPC, Martins IS. Prevalência e fatores associados à síndrome metabólica em usuários de Unidades Básicas de Saúde em São Paulo – SP. Rev Assoc Med Bras. 2012; 58:60-9. 11. Pimenta AM, Andréa Gazzinelli A, VelásquezMeléndez G. Prevalência da síndrome metabólica e seus fatores associados em área rural de Minas Gerais (MG, Brasil). Ciência & Saúde Coletiva. 2011;6:297-306. 12. Phillips AC, Carroll D, Thomas GN, Gale CR, Deary I, Batty GD. The influence of multiple indices of socioeconomic disadvantage across the adult life course on the metabolic syndrome: the Vietnam Experience Study. Metabolism Clinical and Experimental. 2010;59:1164-71. 13. Kivimäki M, Smith GD, Juonala M, Ferrie JE, Keltikangas-Järvinen L, Elovainio M, et al. Socioeconomic position in childhood and adult cardiovascular risk factors, vascular structure, and function: cardiovascular risk in young Finns study. Heart. 2006;92:474-80. 14. Santos CRB, Portella ES, Avila SS, Soares EA. Fatores dietéticos na prevenção e tratamento de comorbidades associadas à síndrome metabólica. Rev Nutr. 2006;19:389-401. 15. Batista EP. A pesquisa qualitativa em Psicologia Clínica. Psicol. USP [periodico na internet]. 2004 [acesso em fevereiro de 2013];15(1-2):71-80. Disponivel em:http://www. scielo.br/scielo.php?script=sci_arttext&pid=S010365642004000100012&lng=en&nrm=iso&tl ng=pt

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16. Fernandes AM, Casonatto J, Destro-Christófaro DG, Ronque ERV, Oliveira AR, Freitas Junior IF. Riscos para o excesso de peso entre adolescentes de diferentes classes socioeconômicas. Rev Asso Med Bras. 2008;54:334-6. 17. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweightand obesity worldwide: international survey. BMJ. 2000;320:1241-3. 18.Antunes HKM, Santos RF, Boscolo RA, Bueno OFA, de Mello MT. Análise de taxa metabólica basal e composição corporal de idosos do sexo masculino antes e seis meses após exercícios de resistência. Rev Bras Med Esporte. 2005;11(1):71-5. 19. VI Diretrizes Brasileiras de Hipertensão.Rev Bras Hipertens. 2010;17:11-7. 20. Zimmet P, Alberti KGMM, Kaufman F, Tajima N, Silink M, Arslanian S. The metabolic syndrome in children and adolescents – an IDF consensus report. Pediatric Diabetes. 2007;8:299-306. 21. Wee BS, Poh BK, Bulgiba A, Ismail MN, Ruzita AT, Hills AP. Risk of metabolic syndrome among children living in metropolitan Kuala Lumpur: A case control study BMC Public Health. 2011;11:333-9. 22. Silveira VMF, Horta BL. Peso ao nascer e síndrome metabólica em adultos: meta-análise.Rev. Saúde Pública. 2008;42:10-8. 23. May R, Kim D, Mote-Watson D. Change in Weightfor-Length Status During the First Three Months: Relationships to Birth Weight and Implications for Metabolic Risk. Am J Phys Anthropol. 2013;150:5-9. 24. Uçar A, Saka N, Bas F, Hatipoglu N, Bundak R, Darendeliler F. Reduced atherogenic indices in prepubertal girls with precocious adrenarche born appropriate for gestational age in relation to the conundrum of DHEAS. Endocrine Connections. 2013;1:112–21. 25. Silva EC, Martins IS, Araújo, EAC. Síndrome metabólica e baixa estatura em adultos da região metropolitana de São Paulo (SP, Brasil).Ciênc saúde coletiva. 2011;16:663-8.

Received on: April 08, 2013 Accepted on: September 30, 2013 Mailing address: Daniel Antunes Freitas Faculdades Unidas do Norte de Minas – FUNORTE Avenida Osmane Brandao, s/n – Bairro JK Montes Claros – MG – Brasil CEP: 39400-000 E-mail: [email protected]

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26. Stabelini Neto A, Bozza R, Ulbrich A, Mascarenhas LPG, Boguszewski MCS, Campos W. Síndrome metabólica em adolescentes de diferentes estados nutricionais. Arq Bras Endocrinol Metab. 2012;56:104-9. 27. Morgenstern M, Sargent JD, Hanewinkel R. Relation between socioeconomic statusand body mass index arch. Pediatr Adolesc Med. 2009;163:731-8. 28. Weiss R. et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med. 2004;350:2362-74. 29. Walker SE, Gurka MJ, Oliver MN, Johns DW, DeBoer MD. Racial/ethnic discrepancies in the metabolic syndrome begin in childhood and persist after adjustment for environmental factors. Nutr Metab Cardiovasc Dis. 2012;22(2):141-8. 30. Mirza NM, Palmer MG, Sinclair KB, McCarter R, He J, Ebbeling CB, et al. Effects of a low glycemic load or a low-fat dietary intervention on body weight in obese Hispanic American children and adolescents: a randomized controlled trial. Am J Clin Nutr. 2013;97(2):276-85. 31. Maffeis C, Pietrobelli A, Grezzani A, Provera S, Tato L. Waist circumference and cardiovascular risk factors in prepubertal children. Obes Res. 2001;9:179-87. 32. Matsuzawa Y, Funahashi T, Nakamura T. The concept of metabolic syndrome: contribution of visceral fat accumulation and its molecular mechanism. J Atheroscler Thromb. 2011;18:629-39. 33. Benmohammed K, Nguyen MT, Khensal S, Valensi P, Lezzar A. Arterial hypertension in overweight and obese Algerian adolescents: Role of abdominal adiposity. Diabetes Metab. 2011;37(4):291-7. 34. Molina MDCB yy. Fatores de risco cardiovascular em crianças de 7 a 10 anos de área urbana, Vitória, Espírito Santo, Brasil. Cad Saúde Pública. 2010;26:909-17. 35. Jin-Ding Lin JD, Lin LP, Liou SW, Chen YC, Hsu SW, Liu CT. Research in Gender differences in the prevalence of metabolic syndrome and it´s components among adults with disabilities based on a community health check up data. Res Dev Disabil. 2013;34:516-20. 36. El-Koofy NM, Anwar GM, El-Raziky MS, El-Hennawy AM, El-Mougy FM, El-Karaksy HM et al.The association of metabolic syndrome, insulin resistance and non-alcoholic fatty liver disease in overweight/obese children. Saudi J Gastroenterol. 2012;18(1):44-9. 37. Romaldini CC, Issler H, Cardoso AL, Diament J, Forti, N. Fatores de risco para aterosclerose em crianças e adolescentes com história familiar de doença arterial coronariana prematura J Pediatr. 2004;80:135-40. Rev. CEFAC. 2014 Jul-Ago; 16(4):1294-1301